The present invention relates to the field of item and peer recommendation algorithms directed towards industry professionals. More specifically, the present invention is aimed at enabling simultaneous search of public information sources and private information sources and providing combined search results.
Most business users turn to public generic search engines such as Google, Bing, Yahoo or the like, to look for answers, resources, products, options, etc. needed to address their business plan points, agendas, informational needs, expert needs, challenges, etc.
Such generic search engines have a few intrinsic advantages. For example, the user can use same search engine for private/consumer and professional/business search activity. In addition, the search query processing benefits from the large scale of such search engines both in terms of statistical tools applied to analyzing the query and the vast number of results which are indexed and available.
However, the large scale aspect of such public generic search engines is, however, a double edged sword. In a business context, the best answer to a search query may reside locally behind a firewall or within non-public databases, which content is not available to the generic/public search engine for indexing. Furthermore, the relevant business environment (company, association, user groups, subscription service, etc.) may have “experts” that can answer the query and/or assist the user beyond the initial question and answer event, hence creating significant business value. Those expert are most likely unknown to the generic search engine since their explicit and/or implicit profiles and activity likely reside behind a firewall and there is no object that identifies them as such experts that can be indexed by the generic engine.
Since a search engine that will identify local answers, documents, resources and experts does not have the large scale advantage of a generic search engine, it would be advantageous to use a “locally optimized” small scale search logic to identify local information, documentation, and experts in connection with a generic global search engine. It would be advantageous to integrate local results from a local search engine (searching non-public information) with the global (public) results from the generic search engine when conducting a search query on a generic search engine.
The methods and apparatus of the present invention provides the foregoing and other advantages.